Research on the Effects of Science and Technology Talent Concentration in the Guangdong-Hong Kong-Macao Greater Bay Area Based on Econometric Methods

Abstract

This study investigates the impact of the science and technology talent policy on the concentration of science and technology talents in the Guangdong, Hong Kong, and Macao Greater Bay Area from 2010 to 2017. Utilizing data from the China Urban Statistical Yearbook and various prefecture-level city statistical yearbooks, the study employs a combination of single-difference and double-difference methods to analyze the effects of the policy. The results indicate that the policy significantly enhances the concentration of science and technology talents in the region, with the double-difference method providing more accurate estimates than the single-difference method. The research further applies the Propensity Score Matching (PSM) and DID methods to address potential selection biases, confirming that the policy’s impact is robust and reliable. Additionally, mediation analysis reveals that the policy's effectiveness is partially mediated by macroeconomic regulation, industrial structure, and demographic factors. The findings underscore the importance of targeted science and technology talent policies in promoting regional talent concentration, offering valuable insights for policymakers aiming to foster innovation-driven development.